Construction Methodology of Modeling Risk Assessment for Typhoon-Collapse Disaster Chain for Public Safety
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摘要:
公共安全是人类社会发展的基础，通过提升公共安全对灾害链的应对能力，来保障社会经济和人员财产的安全.当前，多变的气候特征导致台风-崩塌灾害链对承灾体的安全产生严重威胁.利用知识图谱技术、人工智能技术，融合专家打分法，分析、研究台风-崩塌灾害链中人员、建筑物、交通、财产等承灾体间的关联关系和体系结构，创新性地构建台风-崩塌灾害链风险评估模型.该模型成果，结合台风“杜苏芮”和云梦山公路边崩塌，进行了验证分析.研究结果表明：该模型能够为台风-崩塌灾害链风险评估提供有效的支持，提高了灾害链风险评估的准确性和可靠性，为公共安全领域的灾害风险管理提供了新的方法和思路.
Abstract:Public safety serves as the foundation for human social development. Enhancing the capability to respond to disaster chains safeguards socio-economic activities and protects lives and property. Currently, variable climate patterns pose severe threats to exposed elements via typhoon-collapse disaster chains. This research employs knowledge graph technology, artificial intelligence techniques, and integrates the expert scoring method to analyze, and investigate the correlations and structural systems between exposed elements—such as personnel, buildings, transportation, and property—within typhoon-collapse disaster chains. It innovatively constructs a risk assessment model for these disaster chains. The model's outcomes were validated through case studies of Typhoon Doksuri and a highway slope collapse at Yunmeng Mountain. Findings demonstrate that the model effectively supports risk assessment for typhoon-collapse disaster chains, improving assessment accuracy and reliability. This provides novel methodologies and insights for disaster risk management in the field of public safety.
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Key words:
- public safety /
- typhoon /
- collapse /
- disaster chain /
- knowledge graph /
- artificial intelligence /
- risk assessment /
- engineering geology
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图 2 台风-崩塌灾害链知识图谱构建方法
Fig. 2. Construction methodology of knowledge graph for typhoon-collapse disaster chain
图 5 台风-崩塌灾害链风险评估结果(鹤壁市)
Fig. 5. Risk assessment results of typhoon-collapse disaster chain(Hebi City)
图 6 2023年7月29日云梦山公路边崩塌视频监测
Fig. 6. Video monitoring of the roadside landslide at Yunmeng Mountain on July 29, 2023
表 1 降雨量等级分级
Table 1. Classification of rainfall intensity levels
评估内容 台风引发的降雨 降雨量等级分级 特大暴雨 大暴雨 暴雨 大雨 中雨 小雨 微量降雨(零星小雨) 
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表 2 崩塌危险性评估指标
Table 2. Indicators of collapse hazard assessment levels
发育程度分级 危害程度分级 危险性等级 极其强烈 危害极大 极高 强烈 危害大 高 中等 危害中等 中 弱 危害小 低
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表 3 承灾体易损性评估等级
Table 3. Classification of exposed elements vulnerability assessment levels
承灾体 易损性评估等级分级 人员 极高 高 中 低 建筑物 极高 高 中 低 交通 极高 高 中 低 财产 极高 高 中 低
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表 4 台风-崩塌灾害链风险评估等级
Table 4. Classification of typhoon-collapse disaster chain risk assessment levels
评估内容 风险评估等级分级 台风-崩塌灾害链风险评估 极高 高 中 低
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表 5 台风-崩塌灾害链风险评估指标
Table 5. Typhoon-collapse disaster chain risk assessment indicators
风险等级 风险评估指标值($ {R}_{\mathrm{台}\mathrm{风}-\mathrm{崩}\mathrm{塌}\mathrm{灾}\mathrm{害}\mathrm{链}} $)
(排序范围)极高 (0, 20%] 高 (20%, 40%] 中 (40%, 80%] 低 (80%, 100%] 备注 $ {R}_{\mathrm{台}\mathrm{风}-\mathrm{崩}\mathrm{塌}\mathrm{灾}\mathrm{害}\mathrm{链}} $值系根据公式(4)计算得出
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Cai, W. B., Zhang, J., Tian, J., et al., 2023. Big Data and Artificial Intelligence Technology Help Rapid Assessment of Typhoon Disaster Losses. Disaster Reduction in China, (17): 24-26(in Chinese). Chen, W., 2022. Research and Platform Development of Typical Landslide Disaster Early Warning in the Three Gorges Reservoir Area Based on Deep Learning (Dissertation). China Three Gorges University, Yichang(in Chinese with English abstract). Dong, L. H., 2023. Research on Regional Landslide Warning Model in Fujian Province Based on Artificial Intelligence Algorithms(Dissertation). North China University of Water Resources and Electric Power, Zhengzhou(in Chinese with English abstract). Guo, F., Lai, P., Huang, F. M., et al., 2024. Literature Review and Research Progress of Landslide Susceptibility Mapping Based on Knowledge Graph. Earth Science, 49(5): 1584-1606(in Chinese with English abstract). He, Y. S., Jiang, H. X., 2024. Study on the Temporal Risk Assessment of Typhoon Disaster Chain. Journal of Catastrophology, 39(4) : 213-218. https://doi.org/10.3969/j.issn.1000-811X.2024.04.031 Huang, H. Q., Yu, J., Liao, X., et al., 2019. Review on Knowledge Graphs. Computer Systems & Applications, 28(6): 1-12(in Chinese with English abstract). Huang, J., Wu, X. Y., Wang, H. M., et al., 2024. Mining and Forecasting of Rainstorm Disaster Chain Based on Knowledge Graph. Frontiers of Science and Technology of Engineering Management, 43(4): 46-53(in Chinese with English abstract). Liu, J. J., 2021. Risk Analysis and Assessment of Urban Public Safety Event Chain Based on Complex Network (Dissertation). Hunan University of Science and Technology, Xiangtan(in Chinese with English abstract). Philip, J. W., Veit, B., Nadia, B., et al., 2020. Natural Hazard Risk Assessments at the Global Scale. Natural Hazards and Earth System Sciences, 20(4): 1082-1088. doi: 10.5194/nhess-20-1069-2020 Qiu, Q. J., Wu, L., Ma, K., et al., 2023. A Knowledge Graph Construction Method for Geohazard Chain for Disaster Emergency Response. Earth Science, 48(5): 1875-1891(in Chinese with English abstract). Wang, H., Du, W., Liu, J. H., et al., 2024. Derivation and Transmission Analysis of Urban Flood Disaster Chain Based on Knowledge Graph. Advances in Water Science, 35(2): 185-196(in Chinese with English abstract). Wang, P., 2020. Disaster Chain Mining and Visualization Analysis Based on Knowledge Graph: A Case Study of Geological Disasters (Dissertation). Lanzhou Jiatong University, Lanzhou (in Chinese with English abstract). Wang, R., Lian, F., Yu, H., et al., 2016. Classification and Regional Features Analysis of Global Typhoon Disaster Chains Based on Hazard-Formative Environment. Geographical Research, 35(5): 836-850(in Chinese with English abstract). Wang, S., 2023. Design and Implementation of Regional Disaster Safety Early Warning System Based on GIS Technology (Dissertation). Wuhan Institute of Technology, Wuhan (in Chinese with English abstract). Ward, P. J., Blauhut, V., Bloemendaal, N., et al., 2020. Review Article: Natural Hazard Risk Assessments at the Global Scale. Natural Hazards and Earth System Sciences, 20(4): 1069-1096. https://doi.org/10.5194/nhess-20-1069-2020 Wu, B., 2024. Study on Monitoring and Early Warning Methods of Geological Disasters in Shenzhen (Dissertation). Jilin University, Changchun (in Chinese with English abstract). Ye, J. Y., 2015. Typhoon Disaster Chains Integrated Risk Assessment Model and Information Tupu Based on Multi-Dimensional Matrix (Dissertation). Fujian Normal University, Fuzhou (in Chinese with English abstract). Zhang, C. B., 2022. Risk Assessment of Geological Disasters in Fushun West Open-Pit Mine (Dissertation). Liaoning Technical University, Fuxin (in Chinese with English abstract). Zhang, J. X., Zhang, X. S., Wu, C. X., et al., 2022. Survey of Knowledge Graph Construction Techniques. Computer Engineering, 48(3): 23-37(in Chinese with English abstract). Zhu, H. M., Lin, G. F., Zhang, M. F., et al., 2024. Construction of Typhoon Disaster Chain Knowledge Graph Based on Disaster Risk Survey Knowledge. Journal of Catastrophology, 39(1): 209-215(in Chinese with English abstract). 蔡文博, 张洁, 田杰, 等, 2023. 大数据、人工智能技术助力台风灾害损失快速评估. 中国减灾(17): 24-26. 陈伟, 2022. 基于深度学习的三峡库区典型滑坡灾害预警研究及平台开发(硕士学位论文). 宜昌: 三峡大学. 董力豪, 2023. 基于人工智能算法的福建省区域滑坡预警模型的研究(硕士学位论文). 郑州: 华北水利水电大学. 何玥双, 江辉仙, 2024. 台风灾害链时序性风险评估研究. 灾害学, 39(4): 213-218. 黄恒琪, 于娟, 廖晓, 等, 2019. 知识图谱研究综述. 计算机系统应用, 28(6): 1-12. 黄晶, 吴星妍, 王慧敏, 等, 2024. 基于知识图谱的暴雨灾害链挖掘与预测研究. 工程管理科技前沿, 43(4): 46-53. 刘俊杰, 2021. 基于复杂网络与多维矩阵理论的台风事件链风险分析与评估(硕士学位论文). 湘潭: 湖南科技大学. 邱芹军, 吴亮, 马凯, 等, 2023. 面向灾害应急响应的地质灾害链知识图谱构建方法. 地球科学, 48(5): 1875-1891. doi: 10.3799/dqkx.2022.313 王浩, 杜伟, 刘家宏, 等, 2024. 基于知识图谱的城市洪涝灾害链推演及时空特性解析. 水科学进展, 35(2): 185-196. 王萍, 2020. 知识图谱支持下的灾害链挖掘与可视化分析: 以地质灾害为例(硕士学位论文). 兰州: 兰州交通大学. 王然, 连芳, 余瀚, 等, 2016. 基于孕灾环境的全球台风灾害链分类与区域特征分析. 地理研究, 35(5): 836-850. 王帅, 2023. 基于GIS技术的区域性地灾安全预警系统设计与实现(硕士学位论文). 武汉: 武汉工程大学. 吴博, 2024. 深圳市地质灾害监测预警方法研究(硕士学位论文). 长春: 吉林大学. 叶金玉, 2015. 基于多维矩阵的台风灾害链综合风险评估模型及其信息图谱表达(硕士学位论文). 福州: 福建师范大学. 张超彪, 2022. 抚顺西露天矿区地质灾害风险评价(硕士学位论文). 阜新: 辽宁工程技术大学. 张吉祥, 张祥森, 武长旭, 等, 2022. 知识图谱构建技术综述. 计算机工程, 48(3): 23-37. 朱海铭, 林广发, 张明锋, 等, 2024. 基于灾害风险普查知识库的台风灾害链知识图谱构建. 灾害学, 39(1): 209-215. -
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